Chord

Chord block.

A chord represents flows or connections between several entities or nodes. Each entity is represented by a fragment on the outer part of the circular layout. Then, arcs are drawn between each entity. The size of the arc is proportional to the importance of the flow.

param df:
Input data containing the following columns:

  • “source”

  • “target”

  • “weight”

  • “color” (optional)

  • “opacity” (optional)

type df:

pd.DataFrame()

param color:
Link colors in Hex notation. Should be the same size as input DataFrame.

  • “source” : Color edges/links similar to that of source-color node.

  • “target” : Color edges/links similar to that of target-color node.

  • “source-target” : Color edges/link based on unique source-target edges using the colormap.

  • “#ffffff” : All links have the same hex color.

  • [“#000000”, “#ffffff”,…] : Define per link.

type color:

(default: ‘source’)

param opacity:
Link Opacity. Should be the same size as input DataFrame.

  • ‘source’: Opacity of edges/links similar to that of source-opacity node.

  • ‘target’: Opacity of edges/links similar to that of target-opacity node.

  • 0.8: All links have the same opacity.

  • [0.1, 0.75,…]: Set opacity per edge/link.

type opacity:

(default: ‘source’)

param ordering:
Sort the labels.

  • ‘ascending’

  • ‘descending’

  • ‘’: Do not sort

  • [‘label1’, ‘label2’, ‘label3’]: Custom sort. Note that all labels shoul be included only once for the best result.

type ordering:

(default: ‘ascending’)

param fontsize:

The Fontsize.

type fontsize:

int, (default: 8)

param arrowhead:
The head of the arrow.

  • -1: No arrow

  • 10: default

  • 50: The larger the more pointy the arrow becomes

type arrowhead:

int, (default: 10)

param cmap:
colormap is only used in case color=None. All colors can be reversed with ‘_r’, e.g. ‘binary’ to ‘binary_r’

  • ‘tab20c’, ‘Set1’, ‘Set2’, ‘rainbow’, ‘bwr’, ‘binary’, ‘seismic’, ‘Blues’, ‘Reds’, ‘Pastel1’, ‘Paired’, ‘twilight’, ‘hsv’

type cmap:

String, (default: ‘tab20’)

param title:
Title of the figure.

  • ‘Chord’

type title:

String, (default: None)

param filepath:
File path to save the output.

  • Temporarily path: ‘d3blocks.html’

  • Relative path: ‘./d3blocks.html’

  • Absolute path: ‘c://temp//d3blocks.html’

  • None: Return HTML

type filepath:

String, (Default: user temp directory)

param figsize:
Size of the figure in the browser, [width, height].

  • [900, 900]

type figsize:

tuple

param showfig:

  • True: Open browser-window.

  • False: Do not open browser-window.

type showfig:

bool, (default: True)

param overwrite:

  • True: Overwrite the html in the destination directory.

  • False: Do not overwrite destination file but show warning instead.

type overwrite:

bool, (default: True)

param notebook:

  • True: Use IPython to show chart in notebook.

  • False: Do not use IPython.

type notebook:

bool

param save_button:

  • True: Save button is shown in the HTML to save the image in svg.

  • False: No save button is shown in the HTML.

type save_button:

bool, (default: True)

param reset_properties:

  • True: Reset the node_properties at each run.

  • False: Use the d3.node_properties()

type reset_properties:

bool, (default: True)

returns:

  • d3.node_properties (DataFrame of dictionary) – Contains properties of the unique input label/nodes/samples.

  • d3.edge_properties (DataFrame of dictionary) – Contains properties of the unique input edges/links.

  • d3.config (dictionary) – Contains configuration properties.

Examples

>>> # Load d3blocks
>>> from d3blocks import D3Blocks
>>> #
>>> # Initialize
>>> d3 = D3Blocks()
>>> #
>>> # Load example data
>>> df = d3.import_example('energy')
>>> #
>>> # Plot
>>> d3.chord(df)
>>> #

Examples

>>> # Load d3blocks
>>> from d3blocks import D3Blocks
>>> #
>>> # Initialize
>>> d3 = D3Blocks(chart='Chord', frame=False)
>>> #
>>> # Import example
>>> df = d3.import_example('energy')
>>> #
>>> # Node properties
>>> d3.set_node_properties(df, opacity=0.2, cmap='tab20')
>>> d3.set_edge_properties(df, color='source', opacity='source')
>>> #
>>> # Show the chart
>>> d3.show()
>>> #
>>> # Make some edits to highlight the Nuclear node
>>> # d3.node_properties
>>> d3.node_properties.get('Nuclear')['color']='#ff0000'
>>> d3.node_properties.get('Nuclear')['opacity']=1
>>> # Show the chart
>>> #
>>> d3.show()
>>> # Make edits to highlight the Nuclear Edge
>>> d3.edge_properties.loc[(d3.edge_properties['source'] == 'Nuclear') & (d3.edge_properties['target'] == 'Thermal generation'), 'color'] = '#ff0000'
>>> d3.edge_properties.loc[(d3.edge_properties['source'] == 'Nuclear') & (d3.edge_properties['target'] == 'Thermal generation'), 'opacity'] = 0.8
>>> d3.edge_properties.loc[(d3.edge_properties['source'] == 'Nuclear') & (d3.edge_properties['target'] == 'Thermal generation'), 'weight'] = 1000
>>> #
>>> # Show the chart
>>> d3.show()

Examples

>>> # Change the order of the labels.
>>> #
>>> # Load d3blocks
>>> from d3blocks import D3Blocks
>>> #
>>> # Import example
>>> df = d3.import_example('energy')
>>> #
>>> # Custom order of the labels
>>> d3.chord(df, ordering=np.sort(np.unique(df['source'].values)))
>>> #
>>> # Sort Ascending
>>> d3.chord(df, ordering='ascending')
>>> #
>>> # Sort Descending
>>> d3.chord(df, ordering='descending')
>>> #
>>> # Do not sort
>>> d3.chord(df, ordering='')

References

Input Data

The input dataset is a DataFrame with three column, source, target and weight.

#       source       target  weight
# 0      Aemon        Grenn       5
# 1      Aemon      Samwell      31
# 2      Aerys        Jaime      18
# 3      Aerys       Robert       6
# 4      Aerys       Tyrion       5
# ..       ...          ...     ...
# 347   Walder        Petyr       6
# 348   Walder       Roslin       6
# 349   Walton        Jaime      10
# 350  Ygritte       Qhorin       7
# 351  Ygritte  Rattleshirt       9

# [352 rows x 3 columns]

Chart